Technology for Conquering Chaos - Keynote at the 2013 Design Management Conference

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In a world where complexity is rising, innovations cycles are shrinking, and the rate of change is accelerating, what new technologies must we develop to help us adapt? "Technology for Conquering …

In a world where complexity is rising, innovations cycles are shrinking, and the rate of change is accelerating, what new technologies must we develop to help us adapt? "Technology for Conquering Complexity" introduced the conference audience to an emerging technology frontier known as community computation. It showed how this new field will enhance our innovation process, help us make sense of complexity, and help us solve some of the most complex challenges of our time.

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  • 1. A Common FutureDMI 2013Leland the last decade, Iʼve been fascinated by four emerging areas: the science of complexity, the commons movement, peer-to-peer networks, and bio-inspired computation. Insmall and large ways, these four domains offer important insights into the others. As we think about designing our economy each will exert an influence on policy, organizationalstructures, concepts of property, concepts of technology, and social relationships. My talk today drills down into one overlap between these four domains.
  • 2. The best place to begin is where I grew up. I grew up in Alpharetta, a small town 45 minutes north of Atlanta, GA. Itʼs a big town now, but, at the time, it was tiny.
  • 3. To give you a sense of how small it was, this was our city hall. Itʼs not much, but in the context of Alpharetta, it was one of the larger and more iconic building. My parents knew asmall southern town was a great place to raise three boys, but they also knew it had a major drawback. It didnʼt afford their children exposure to new people, perspectives,cultures, and opportunities.To counter this, my parents made sure to feed us lots of diverse materials anytime my brothers and I showed any interest in a subject.Taking after my mom, I loved history. Feeding that enthusiasm, my parents took our family to the best place to learn about American history: Boston.
  • 4. My family and I walked the Freedom Trail throughout Boston. We pasted through Beacon Hill...
  • 5. ... and visited where the revolutionaries had the Declaration of Independence. We continued on our tour by taking a right from here and thatʼs when I froze. I distinctly rememberthis moment where a 9-year-old me became frozen in awe as I stood and looked at this...
  • 6. As many of you know, this is Boston City Hall. Itʼs an excellent example of Butalist architecture – style inspired by Le Corbusier and born from the British architects Alison and PeterSmithson. Coined in 1953, the term comes from the French phrase “beton brut” or “raw concrete. it was a phrase used by Corbusier to describe the poured board-marked concretewhich he constructed many of his post WWII building. The style gained considerable momentum in the United Kingdom and flourished up through the 1970s.
  • 7. Itʼs a style easily identified by its exposed structural elements, rectilinear form, epic proportions, and repetitive geometric forms.But at nine years old, I knew none of this. All I knew was that this building was awesome. It looked like it came from Star Warts – which helped give it a futuristic sensibility. Iwanted to touch the building, walk into it, walk around it, ask questions about it. Everything that I had hoped to see in Boston went on the back burner. All I cared about was thisbuilding.
  • 8. Upon our return to Alpharetta, my parents bought be tons of books on Brutalism. At nine and ten years old, i was reading book by Reyner Banham and seeing glimpses of thefuture like this one.Image; The University of California, San DiegosGeisel Library 1970
  • 9. Every page I turned was another glimpse of what the future would look like.Image right: Panum Institute
  • 10. Each vision was more beautiful than the last. Louie Kahn, the creator of the The Salk Institute and other, became my favorite.Image: Salk Institute, La Jolla CA 1965
  • 11. Iʼd often look out my bedroom window in Alpharetta and imagine a building like this rising over the pine trees.Image: National Assembly Building, Dhaka, Bangladesh 1962
  • 12. That one day Iʼd check out book here.
  • 13. That one day Iʼd see a play in the park here.
  • 14. That one day Iʼd go to church here.
  • 15. That one day Iʼd work here.And I attribute this experience as the reason I entered design. I wanted to make this world. I thought I could make this world. I had to rational reason to believe that I could do it. Iwas just excited to do it. And for me, that was enough.
  • 16. A vision of the futurecompels us beyond our limits.And I think this is the great power of visions of the future. Whether youʼre a nine year old or a thirty nine year old, visions of the future make us believe we can achieve so muchmore than we ever thought. They fill us with effusions of excitement that compel us beyond our limits.Like architecture, the future represents a higher ideal which we charge after. It calls upon the best in us, and gives us parameters to act.
  • 17. Whether its a vision of a new government where the king serves the people...
  • 18. ... or a vision of walking among the stars...
  • 19. ... or a vision of traveling through a virtual reality...
  • 20. ... or being a member of a McLuhan-esque global tribe, visions of the future compel us beyond our limits and call upon the best of ourselves.
  • 21. ExplorersIn doing so, the posture we take towards the world is that of and explorer – a person who believes the best is ahead of them. The explorer believes that there is something to befound and they will be the ones to find it. It is optimistic. It is eager. It is a desire to move beyond limits.
  • 22. I return to this book by Thomas Friedman because he wrote it in 2005.
  • 23. I find it interesting that three years later he wrote this book – Hot, Flat, and Crowded. In this book, he criticizes the same values he praised in the first book, The World is Flat. hewrites that if we continue to promote and live by those values, we will push society past a threshold we cannot revert. We will, in short, push society off a cliff. Friedman saw theworld as it is and as it would be and he was terrified of what he saw.Itʼs not just Friedman who proffers these pessimistic visions. Not a week goes by that Hollywood is not releasing a new film that dramatizes how the world will it.The visions are as wide ranging as they are vivid.
  • 24. Nuclear annihilation.
  • 25. Cataclysmic weather events.
  • 26. The total collapse of society after peak oil.
  • 27. The drought, famines, and wars caused by loss of clean, free, and abundant drinking water.
  • 28. Primate usurpations.
  • 29. A world of extreme economic disparity and abuse.
  • 30. Plagues.
  • 31. And of course, alien invasions...
  • 32. ...alien invasions...
  • 33. ...alien invasions...
  • 34. ...and zombie apocalypses.
  • 35. This obsession with our own end of times is so palpable, so engrained in how we think about tomorrow, that even that “Happiest Place on Earth” cannot imagine the future withoutit being dystopic.One could argue that this is entertainment and Dystopiaʼs create a good premise for conflict – which is the source of entertainment.I agree. To a certain extent.For thing, dystopiaʼs are not the only source of conflict. There are many many other sources to choose from in creating entertainment.But most importantly, itʼs critical to remind ourselves that a culture is defined by the stories we tell ourselves. Stories influence us in soft, and subtle ways which are hard to noticeuntil we finally notice that something has changed. To put it more bluntly, if we continue to tell stories of societal death, destruction, and fear, then we will live according to thosenarratives.
  • 36. If you go into Costco today, you will already see how this entertainment narrative has become a narrative of our daily life. This is a clipping from Costcoʼs circular. It is a listing for aproduct called Shelf Reliance – a disaster food supply to store when all food supply options are eliminated. In other words, its the brand that prepares you for a dystopic future...
  • 37. ...even if youʼre a vegetarian.
  • 38. ExplorersAs a result, our collective mindset is shifting from that of an “explorer” – where we are optimistic about the future and seek it out – to...
  • 39. Survivors...that of an “Survivor – where we are terrified of the future and our only ambition is to insulate ourselves from it as best we can.This is a dangerous shift.
  • 40. Where there is no vision,the people perish.Proverbs 29:18Because a society is only as strong as its vision of the future. And when there is no vision, the society perishes. This is ancient wisdom.
  • 41. What could we explore?Because of this shift Iʼve noticed, Iʼve been consumed by this question, “What could we explore?” Not “what SHOULD we explore?” but “what COULD we explore?” Iʼm looking forthat vision that compels us beyond our limits and makes us explorers again.This is the crux of my talk today. This is the question I hope to answer.
  • 42. To guide us in the journey, let me introduce you to this guy: Jaron Lanier. Jaron is a smart fella. Heʼs a research fellow at Microsoft Research Labs, was an early pioneer of virtualreality, and, in 2010, Time magazine named him one of 100 the most influential people in the world. Now Jaron doesnʼt offer a vision of the future. Instead, he frames how weshould think about that vision.
  • 43. A vision of the future must be:1. Challenging2. Filled with fascination3. Unpredictable or not automatic4. Filled with achievement5. Non destructive or perilous6. Demanding of our creativitySpecifically, he says that a useful vision of the future must meet this criteria. I love this list, because at that heart of it is this idea...
  • 44. Any useful idea about the future shouldappear to be ridiculous in the present.Everything wonderful, amazing we experience right now had to sound absurd when it was first discussed.Now that we know that, what is an ridiculous future we could be exploring right now?
  • 45. 1994To introduce you to it, letʼs go back to 1994. What Iʼm about to show you is something made in that year and, when I first saw it in the late 90s, captivated me. I didnʼt know what itwas but I loved it. I didnʼt have the language or models to understand it. Only in the last five years or so have I come to understand the profound implications of it. What I saw wasthis...
  • 46. What youʼre looking at is an art piece. it was created by Karl Simms in 1994. Karl had created a collection of 3D creatures, composed of 3D blocks, that can swim in a 3Denvironment.Link to video:
  • 47. Evolutionary AlgorithmA computer simulation of the evolutionary process that evolvessolutions to complex design problems.To do this, we was playing with an Evolutionary Algorithm. Evolutionary Algorithms were concepted in the 1970s by a John Holland but didnʼt really become useful until the 1990swhen computer processing power and efficiency caught up with the demands of the algorithm. What this algorithm does is simulate the evolutionary process inside a computer.And, if you know anything about evolution, you know that evolution is a process that evolve solutions to complex design problems. It can efficiently search a large sample space ofalternative, possible solution to find a satsificing solution in a relatively short period of time.
  • 48. Itʼs important to reiterate that Karl Simms didnʼt create these creatures. He created a computer algorithm that evolved these creatures from crude designs that had low swimmingeffectiveness to more complex designs that had high swimming effectiveness.
  • 49. And it wasnʼt just one solution. Evolutionary algorithms produce a huge population each showcasing novel solutions to the problem of swimming.
  • 50. POPULATE SELECT INNOVATION(Recombination/Mutation)FITNESS1. 2. 3. 4. 5.EVALUATEA GENERATIONYou can code out this process and that code can be of varying complexity depending on what youʼre trying to evolve. But no matter what, that process breaks down into 5 stages.The first stage if “Fitness.” “Fitness” relates to Darwinʼs concept of “Survival of the fit.” Think of “fit” as meaning “success criteria.” Every environment or problem has a set ofcriteria that the organism or solution must meet. If an organism doesnʼt, it dies. If a solution doesnʼt, it is discarded when a better solution is found. Stage 2 is “populate.” Everyevolutionary process requires an initial diverse population of organisms or solutions. Stage 3, “Select,” is when a pair of possible organisms/solutions are chosen for mating –essentially its choosing a male and female. Stage 4 “Innovation” is when the male and female swap chromosomes and birth a child. That child, in stage 5 “Evaluate,” is thenmeasured against that initial fitness criteria, tagged, and returned to the population. To run through this whole process once is called a generation. Typically, computers run throughhundreds, even thousands of generations trying to evolve the best answer to the solution.
  • 51. FITNESS1.POPULATE2.SELECT3.INNOVATION(Recombination/Mutation)4. 5.EVALUATEMaximumSwimEfficiencyFMCIn Karlʼs art piece, the fitness was maximum swim efficiency. His population was a collection of 3D creatures with varying fitness levels from which he chose two at random,swapped their chromosomes, and evaluated the fitness of their offspring.
  • 52. Evolutionary algorithms are more popular than you might think.Designers, engineers, and architects have used them for variouspurposes.
  • 53. Architects have used evolutionary algorithms to evolve complex structures that individual human minds couldnʼt comprehend. Others have used evolutionary algorithms to grow, asthis video shows, structures with maximum stability with minimum materials.Link to video: architecture example:
  • 54. People have even used evolutionary algorithms to evolve music. In this example, researchers used the algorithm to evolve music in the style of Bach. To be clear, they were nottrying to copy an existing Bach song. They were trying to have the algorithm create music that sounds like Bach created it. To do it, the researchers broke down the key, definingcharacteristics of Bachʼs music and defined those as the fitness criteria. Now Iʼll play for you three songs and I want you to listen to which one or ones the algorithm created andwhich one or ones Bach wrote.Itʼs really really hard to draw the distinction isnʼt it? I find this immensely to video:
  • 55. Another example comes from GE engineers. Years ago, GE used an evolutionary algorithm to design a jet turbine. The results were amazing. Not only was the algorithmʼs design3x better than any design developed by a team of humans, but itʼs development time was dramatically faster. Human teams typically take 5 years to design a new jet turbine. Thealgorithm took only 2 days.Designing building, writing music, and design jet turbines: these are only a few of the amazing things evolutionary algorithms have accomplished.But while they are good at many things, these algorithms, and computers in general, are really bad at others things.
  • 56. For instance, computers are horrible at meaning and natural language.misc info:
  • 57. “Does she love me?”Computers are also terrible with ambiguousquestion, fuzzy data, and problems that lack clearsolutions.
  • 58. They are also terrible at combining heterogenous data sets to create a new idea – a.k.a. a leap of imagination. I show Twitter because its founder JackDorsey combined the behavior patterns in CB radio culture and the trends in mobile, digital technology to create a leap of imagination called Twitter.
  • 59. Computers are also terrible atspatial reasoning and motionplanning.
  • 60. And finally, no computer can understand this. This video is my favorite. I love it. I consider it to be the most beautiful piece of film Iʼve ever seen. Itʼs spontaneous, intimate,delicate, sweet, and harmonious. Yet no computer can understand that. No computer can understand beauty because computers are terrible with subject values such as “beauty,”“fun,” “cool,” “touching,” etc. No computer can understand this let alone create it.
  • 61. precise definitive numericalSo what happens when the things we want toachieve arent precise, definitive, or numerical?
  • 62. 20 billion neurons200 trillion synapsesThatʼs when you need the raw computational power that comes with 20 billion neurons and 200 trillion synapses.The human brain is the most powerful computation system on the planet.
  • 63. 4.5%To give you an idea how powerful it is, letʼs compare it to IBMʼs Blue Gene - among the most powerful super computers in the world.Even a feat of engineering like Blue Gene can only simulate the computational power of 4.5 percent of the brain.Source:
  • 64. Evolutionary AlgorithmSo when we have to deal with questions and data that are not precise, numerical, or definitive, are evolutionary algorithms – which are run on computers – still useful?
  • 65. Human-Based Evolutionary AlgorithmThey are if we transform them into human-based evolutionary algorithms (HBEA). HBEA combine the processing efficiency of computers with the processing robustness of thehuman brain to create a productive algorithmic process that can tackle problems neither humans nor evolutionary algorithms could alone. It works by having the computer kick outcertain parts of the algorithm to the human user who them performs the computation in their brain and returns that information/solution to the algorithm for continued processing.
  • 66. 1. 2. 3. 4.POPULATE SELECT INNOVATION(Recombination/Mutation)FITNESS5.EVALUATEItʼs structured the same way as a computer-based evolutionary algorithm. The only difference is that a human can define the fitness function, create the initial population, selectwhat to breed, choose which chromosomes to swap, or evaluate the output. Or the human can do all of these functions. In that case, the computer becomes an air traffic controllermoving tasks and data around.
  • 67. This is an old idea.This may sound like a science fiction idea – something that may appear 15 years in the future.But itʼs not. Weʼve been doing this for a very long time.
  • 68. We only need to look at the Native Americanʼs work with the Teosinte plant. The Teosinte plant is a grassy plant that produces hard seeks that, if you were to eat them, would feellike you were chewing on pebbles. Nonetheless, the Native Americanʼs wanted this to become a food source for them. So they defined new fitness criteria for the plant: softer,bigger, juicier, sweeter. They then selectively bred the plant over many generations. The result is our modern day corn. Corn is a solution derived from a HBEA. In fact, culturalanthropologists call it a thoroughly cultural invention. Corn does no grow in the wild. Itʼs survival depends upon farmers planting and protecting it.more here:
  • 69. HBEAs are also used in modern, digital contexts. Pandora, the online music station, is a great example. Pandora bills itself as the music genome project. It takes music and breaksdown itʼs “genetic” components – essentially the elements that make a song a song. And rather than create new music, it tries to find the optimal playlist that has all songs thatperfectly match your music preferences. In other words, it tries to create a string of elements (songs) that matches your fitness criteria (what elements of music you like.) To do this,it selects a song and presents it to you. You listen to the song and evaluate it it. You score determines whether or not that song will continue to stay in the string and what songs itwill add to the playlist string.
  • 70. HBEAs are evolving.These are only a few examples how how weʼve used HBEA for a long period of time.But Iʼve noticed something exciting happening: HBEA are evolving. This is due to five key social and technological trends. Iʼll speak to each one and then review them afterwards.
  • 71. The first trend is “it to bit.” Everything is converting from physical to digital. Media. Medicine. Manufacture. Everything that was once made of atoms will be made, predominantly, ofbits as we move forward. This narrative is nothing new. Weʼve heard all this before. However, Iʼd like to add one new perspective to this. What is of absolute importance is not somuch that everything is going digital. What is of absolute importance is that when everything is digital is we become digital geneticists. When the content and infrastructure of oursociety is composed of bits, that means that the DNA of our culture – the stuff the defines the form and process of our culture – is digital. This digital DNA is much easier, faster, andcheaper to access, manipulate, share, and restructure than organic DNA.
  • 72. 0306090120‘09 ‘10 ‘11 ‘12 ‘13 ‘14 ‘15Source: IHS iSuppliConsumer Spending on Cloud Computing(Billions of U.S. Dollars)The second trend is the publicʼs accelerating adoption of cloud computing. Cloud computing liberates digital DNA. It frees it form limitations of location, user, time, or size. Withcloud computing we can share huge cacheʼs of digital DNA with everyone, all at once, all over the world. Someone in India can work with a petaflop of data uploaded ten minutesago by a company in Wisconsin – while the employees in Wisconsin work on that same data set at the same time. Cloud computing makes that possible.
  • 73. The third trend is social media. I hesitate to bring this one up because it sounds so trite. But it has created some important elements of our modern experience. Most importantly,itʼs created a new communication architectures that allows to have conversations not with 1 person or a team of people, but with a community of people. We can talk withthousands of people at once as never before. In doing so, weʼre developing whole new social norms and protocols for doing so. We are literally recoding our social norms to adaptto a world of massive, asynchronous communication – and many cognitive scientists believe we are rewiring our brains as well. In this context, we are exposed to more ideas,more information, and more inspiration.
  • 74. On PremiseThe fourth trend is the shift in softwareʼs business model. Traditionally, software has followed the “on premise” model. This meant that youbought a disk and installed the software on your computer – literally keeping it “on premise.” That software did not exist on any other computer.
  • 75. SaaSThe new model is called “software as a service.” In this model, there is no disk. Thesoftware exists in the cloud. You access it through the Internet by buying a subscriptionto it.
  • 76. “The subscription pricingsaves users from paying fourfigures up front – and makesCreative Suite programsaccessible to a wideraudience.”“Adobe Embraces The Cloud, LaunchesSaaS Version of Their CS 6 Suite”DreamSimplicity.comAdobe a recent notable player whoʼs made this transition. What happens when software shifts from on premise to Saas is that a four-figure, highly powerful, professional gradesoftware becomes dirt cheap in comparison. Not only that, it becomes easier to distribute. In this emerging reality, more people will have access to more powerful software. Thisdemocratization of professional grade software will enable more people to manipulate the digital DNA to create the ideas theyʼve developed through social-media-drivenconversations.
  • 77. 50%202020%2012The fifth and final trend is the growth of the freelancers in the workforce. Another term for this is the “contingent” workforce. Today, contignet workers compose 20% of theworkforce. That number will reach 50% in 2020. This is has big implications. No longer will the workforce be rigidly locked into jobs that have them perform the same tasks againstthe same problems for years. The workforce will become increasingly flexible. Individuals will be able to take on different jobs from different companies, deploying a range of skillsagainst a range of problems. But most importantly, this fragmentization of the workforce will allow individuals to form ad hoc structures best tailored to the individual task orchallenge. “Tiger teams” of freelancers will become the common alliance of workers within companies as full-time employees dwindle in importance.Rise of “Freelance Nation” / “Gig Economy”The Contingent work force
  • 78. Five key trends1. It to bit2. Adoption of cloud computing3. Social media driven collaboration4. Conversion to SaaS5. Shift to contingent workSo here are those trends again. The impactof these trends is an evolution of HBEA....
  • 79. For the first time, HBEAs can bemassively collaborative and scalable.For the first time, HBEAs can bemassively collaborative andscalable.
  • 80. Human-Based Evolutionary AlgorthimThis means that a new kind of evolutionary algorithmis branching off, in an evolutionary sense, from HBEA.
  • 81. Community-Based Evolutionary AlgorithmAn algorithm for coordinated creationamong distributed humans and computers.Human based evolutionary algorithms are becoming community-based evolutionary algorithms (CBEA). Iʼve listed a working definition. But the idea is that rather than having onehuman interact with a computer in an algorithmic relationships – as HBEAs do – a CBEA has hundreds of people interacting with hundreds of computers. This new algorithmicprocess integrated the processing efficiency of computers with the processing robustness of the human mind and integrates that with the collective intelligence of community. Theresult in a new kind of technology capable of doing what no computer, human, or community could do alone. I believe this has profound implications on value creation andinnovation in our 21st century economy.
  • 82. ChairsTo help us understand those implications, Iʼd like to take a slight detour.Whenever a significant new technology or means of production enters the world, who are the first people to play with it and explore it? Go back 100 years and youʼll see that atevery point, itʼs been designers. Theyʼre concern is always finding an answer to one question: How can I use this technology to improve the world?And, as they explore that question, what is one of the first things they make? They make chairs.
  • 83. Plywood ChairCharles, Ray EamesWassily ChairMarcel BreuerBone ChairJoris LaarmanArmchairPeter ShireThe Bauhaus had the Wassily Chair, California Modernism has the Eamesʼ Plywood Chair, the Memphis design movement in Italy had itʼs Armchair, the the bio-mimetic movementhad the Bone Chair.Chairs are remarkably wonderful objects that are familiar but have an infinite number of configurations. While not the most technologically advance piece of technology, they areperfect symbols of the opportunity and philosophic ideals embedded in the technology.
  • 84. Can a CBEA design an innovative chair?Knowing this, itʼs not surprising that researchers at the StevensInstitute of Technology asked if a CBEA could design an innovativechair.
  • 85. 1. 2. 3. 4.POPULATE SELECT INNOVATION(Recombination/Mutation)FITNESS5.EVALUATEThe researchers followsthe same 5 step process.
  • 86. FitnessInnovative designs rate high onoriginality and practicalityThe defined fitness as a chair thatrates high on originality andpracticality.
  • 87. They then recruited a few thousand people. None of them were designers. None of the had sophisticated understanding of design or competence in professional grade designtools. They were just everyday people.The researchers asked the participants to use Google Sketch (A free Saas) to draw a chair. It didnʼt matter the style, or the the design. Any chair would be fine.
  • 88. These drawing served as theinitial population for the CBEA.
  • 89. Researchers then askedparticipants to select twochairs.
  • 90. Participants then selected key elements from the chosen chairs anddrew a new chair showcasing the combination of those elements.
  • 91. 1 2 3 4 5 6 7Not original Extremely originalNot practical Extremely practicalFinally, participants rated the outputs against originality and practicality.Those chairs were tagged with a score and dropped back into thepopulation.
  • 92. 1. 2. 3. 4.POPULATE SELECT INNOVATION(Recombination/Mutation)FITNESS5.EVALUATEAs I mentioned before, these algorithms – when run on computers – go through hundreds –if not thousands – of generations. This experiment only went through three generations.
  • 93. Generation 1 Generation 3PROPORTION OF “INNOVATIVE” DESIGNS0. howʼd they do? Well the question was “could a CBEA design an innovation chair?” in evolutionary algorithm terms, itʼs more accurate to say “could a CBEA design MOREinnovative chairs with each successive generation?”The analysis proved they could. By generation three, the number of innovative chairs per generation had more than doubled.
  • 94. Here is one of those innovative generation three chairs. It doesnʼt look like much, but thatʼs not the point. The point is that the algorithm had helped a community of non-designersbe more innovative in their designs.If we ran this same process with a community of talented, experienced designers – be they a large team inside a company or a community of freelancers – would CBEA processhelp them produce a truly remarkable chair that all of us at this conference would agree to be “innovative”? I think so. Who we use in these algorithms matter.
  • 95. Researchers have applied CBEAs to more than design innovation. Theyʼve also applied it to healthcare – specifically nutrition. As we all know nutrition is a big issue in our country.The ideal situation would one in which everyone had a nutritionist helping them make optimal decisions. But not everyone can afford a nutritionist and, even if they could, therearenʼt enough nutritionists to go around.Thatʼs why researchers created this: Platemate. Platemate is a CBEA that transforms a community of people into virtual personal nutritionist.If youʼre a user, you take a picture of your food with your phone and upload it into this program. Platemate them moves your picture around to a variety of people participating inthe CBEA. They judge and log the portion size, calorie count, fat counts, carb count, sugar count, and nutrient information. Overtime they can learn what youʼre eating too much ofand what you need to eat more of. They then send you a recommendation of how to evolve your next meal to create a healthier balance. The idea is that your diet evolves to anoptimal diet.
  • 96. Another great example of a CBEA is GitHub. GitHub is a online site that invite coders to post and share their working code. Other members can edit your code, collaborate withyou on it, combine code, “fork it” (which means branch off of it, and more. The whole experience is loosely based on a CBEA. The idea is to post a crude piece of code and thecommunity, through an iterative process, works together to evolve it to a more refined, highly fit piece of code.Iʼve just shown you three things CBEAs can do. They help us improve design innovation, create and deliver new services, and serve as a new model for value production.But Iʼd like to show you one more.
  • 97. It has to do with this guy. This is the M-PMV retroviral protease. It is responsible for the reproduction of an AIDS-like virus in rhesus monkeys. Medical researchers believe that ifthey can discover how to stop this protease, they can hopefully do the same in the human version.To do this, they have to design a chemical key, that when inserted into the protease, will turn it “off.” The first step in designing any key is knowing the structure of the lock itʼsmeant to fit. The same criteria goes for this chemical key. Researchers need to know the exact structure of the M-MPV to design the chemical key. That sounds like an easy task,“Find the structure of the protease,” but itʼs actually one of the hardest in all of medical science because...
  • 98. 10,000,000,000,000,000,000,000,000,000,000possible configurations...there are these many possibly configurations. And the researchers only need to find one – the one configuration that exhibits the greatest energy efficiency. Theoretically, youcould go sequentially sample all available configurations until you found the right one. But there is no guarantee that the right one wonʼt be the last one. And if it was the last one, itwould take longer than the age of the universe to get to it.source:
  • 99. 30 yearsFor thirty years, researchers have tried all imaginable efforts to efficiently find the right configuration. Theyʼvethrown money, PhDs, super computers, and specially designed computer algorithms at it. But nothing hasworked.
  • 100. Itʼs been extremely frustrated for all involved. In fact, a team at the University of Washington was at their wits its. They literally said that they weregoing to try one more idea - “a list ditch effort” – solve this. If it didnʼt work, they were going to have to move on to another scientific challenge.
  • 101. Their idea was to see if a CBEA could find the solution to the problem. They game the CBEA the interface of a game and called it FoldIt. FoldIt did not invite medical researchers,medial students, or, more generically, people with biology degrees to solve the protein structure. It invited people who loved to play games and solve puzzles to participate in theCBEA.
  • 102. The game existed online. Players would bend and twist a three dimensional representation of the M-MPMV protease searching for its high energy efficiency configuration. Playerscould play alone, play in teams, copy other teams strategies, join to team, and so on. It was highly collaborative. When they felt they had a highly efficient configuration they alertedthe UW team who tested the configuration – or, in evolutionary algorithm language, evaluated the fitness of the link:
  • 103. 30 yearsWhat researchers and specialcomputers could not solve in thirtyyears...
  • 104. 3 weeksCBEA participants solved in 3 weeks.I find this immensely inspiring because what is shows us is that CBEAs are not only good for design innovation, service deliver, and value production, but they can also aid us insolving some of the most complex problems our society faces.
  • 105. WTF. This is just crowdsourcing.Itʼs at this point that I need to address Iʼm sure everyone in the audience is thinking right now: “WTF. This is just crowdsourcing.”Iʼd like to argue that itʼs not. Iʼd like to argue that we toss around the term crowdsourcing way too much and apply it too way too many things. In doing so, it obscures our attentionfor the subtleties and nuances of emerging ideas that look like crowdsourcing but are not at all crowdsourcing. I believe that crowdsourcing and CBEAs are two distinctly differentideas. To help draw out that distinction, here are a few comparisons.
  • 106. On the left you see an example of crowdsourcing. Itʼs an art project by Aaron Koblin. Aaron asked people on the Internet to draw a sheep and send it to him. Thatʼs it.On the left, you see an example of a CBEA. FoldIt is an iterative process where people collaborate with each other to solve a problem.
  • 107. On the left is an example of crowdsourcing. Itʼs called My Starbucks Idea. It invites people on the Web to send Starbucks their ideas about how to make Starbucks better.Starbucks may or may not act on any submitted idea. This is essentially an online suggestion box.On the left is an example of a CBEA. GitHub is an online site that allows people to post their code-based ideas and work with other people on the site to improve the ideasovertime.
  • 108. Crowdsourcing CBEANo computation performedSingle actionBest for amassing a hugepopulation of data or optionsComputation performedIterative algorithmic processBest for creating innovativesolutions to problemsTo be specific, here are the differences I see between crowdsourcing and a CBEA. Crowdsourcing asks participants to perform a single action. Send us a drawing of sheep. Postyour suggestion. And thatʼs it. Thatʼs the extent of the participants involvement. A CBEA is an iterative algorithmic process that invites participants to collaborate with each other toimprove each others work.In crowdsourcing, no computation is performed. No information is transformed. In a CBEA, by the very nature of improving peopleʼs ideas and trying to evolve information to solvea problem, computation is performed.Crowdsourcing is best for amassing a huge population of data and options – of varying degrees of quality, usually poor quality. A CBEA is best used for creating innovativesolutions to problems.
  • 109. Evolutionary AlgorithmBut a CBEA, as a modification of a evolutionary algorithm, solves only certain kinds of problems. The world isfilled with a huge variety of problems that an evolutionary algorithm cannot solve – even if it is community based.
  • 110. Reaactive Search Immune Network Algorithm Random Forest AlgorithmVariable NeighborhoodSearch Cuckoo Search PerceptronBee Algorithm Firefly Algorithm Winnow AlgorithmBat Algorithm Evolutionary Algorithmk-Nearest NeighborAlgorithmDendritic Cell Algorithm Harmony SearchLearning VectorQuantizationScatter SearchParticle SwarmOptimization C4.5 AlgorithmTaboo Search Ant Colony Algorithm ID3 AlgorithmSimulated Annealing Hill Climbing Algorithm BrownBoostThe exciting thing for me to think about it all the other algorithms out there. These algorithms solve different sorts of problems in different ways. Itʼs exciting to think about how eachof these might be enhanced – and their applications expanded – if they became community based.The really cool thing Iʼm hinting at is the theory that community is technology. Just as we run all sorts of algorithms on computers today, we will run all sorts of algorithms oncommunities tomorrow. We will interact with communities just as we interact with computers today. In the future we will interact with community through an interface. The interfacewill send out algorithms to a community of people weʼve selected to perform a specific task. And this future isnʼt as far off as you may think.
  • 111. Already researchers are exploring what those community interfaces may look like. This product is called Soylent – a tongue-in-cheek name that reminds you, itʼs people inside.Hereʼs how it works:imagine youʼre a freelance journalist and youʼve just finished your article and you want someone to proof read it. As we know today, Microsoftʼs built-in grammar and spell checkeris terrible. Your new option is the top left button that says “crowdproof.” This button invites a community of people to proof read your work. The second button in, “Shortn,” invitesthe community to help you tighten your writing by editing out unnecessary or redundant sentences. If you need something else performed on your writing, you can click the thirdbutton “Human Macro” to create your own algorithm to have the community run.
  • 112. Even Adobe has explored community interfaces. What you see here is a collaboration between MIT and Adobe. The idea here is to create a creative tool that makes use of acommunity. The box on the left, box a, is what the individual user has created. Think of it as the raw material that the community algorithm will compute/transform. The middleboxes, b and c, are the rules the individual user has written. These rules define the actions the user wants the community to perform on the object in box a. Box d is a windowshowcasing what the community has produced in accordance with the rules set in box b and c. This third box is an excellent feedback mechanism showing the user what his rulescreate. If the output is not meeting the users idealized fitness criteria, (s)he can adjust the rules to optimize the communityʼs output. As you can see from the box on the left, theambition in this example is to create a dance party by manipulated the man image on the left.Source:
  • 113. So what?Iʼm completely fascinated by this frontier. But maybe you find it to be merely a cute technological oddity and arenʼt quite sure how it fits in thelarger picture of the economy. Thatʼs a fair question given the topic of this conference is “Designing the Next Economy.” So how does it fit?
  • 114. 67 years 15 years1920s 2010sIn the 1920s, a company listed on the S&P 500 could expect to stay on the last list a cushy 67 years. Today, that number has plummeted to fifteen years. In some industries its ten.By 2020, analysts predict that 75% of the companies listed on the S&P 500 will be companies weʼve never heard of today. That is an incredible amount of turnover among somevery large companies.
  • 115. 1800s50 years1900s20 years2000s5 yearsBusiness historians have also looked at the frequency of when disruptive technologies have been introduced into industries. The 1800s, an industry could expect 50 year periodsbetween significant technological disruption. When these disruptions did hit, they rolled out slowly and experience very few significant alterations over the years. It was just anexpensive and labor intensive process. By the 1900s, the frequency of disruptive technology dropped to 20 year intervals. Today that number has dropped to 5 years. This meansthat every 5 years, a new disruptive technology hits industries – and hits them hard. Every five years, new rules, new challenges, new competitors, new questions, newinformation, new worlds confront us. That is a lot to handle that often.We live in an age of acceleration.Source:
  • 116. 50% of what we sell didn’t exist5 years ago.50% of what we will sell in 5 yearsdoesn’t exist now.If you’re still doing what you did 5years ago, please stop.You’ll break the company.Cargil executiveBusiness now exists in this absurd situation where any individual product, service, advertising campaign, or understanding of the marketplace rarely, if ever, maintains a competitiveadvantage for more than a year.I love this quote from a Cargil executive. Itʼs comes from a sign in his office and perfectly sums up this absurd reality.
  • 117. AnxietyChange has always generated anxiety. But it feels different now. This new reality demands that we reinvent ourselves on a continuous basis not to maintain thought leadership ormarket share, but just to survive. Every five years, generations of hard fought knowledge, hard fought business models, hard fought product designs, and hard fought marketintelligence are being overturned. Reality is outpacing any one personʼs ability to keep up. When we canʼt keep up, we lose our our sense of balance. Everything seems disjointed.Confusing. We all feel dizzy. We feel nauseas. We feel....
  • 118. There is a sense of loss, of suddenexile – a feeling that one’saccumulated culture or experienceis devalued, leaving one exposed tospiritual destitution.Leo SteinbergArt critic and historian...a kind of existential crisis. Our understanding of the world is not keeping pace with the world. There is a collective sense that progress is no longer possible because our presentchaos seems untameable and growing complexity. We believe it will only get worse in the future.I believe that this is where our fatalist attitude about our future comes from. It comes from our inability to make sense of our present – our growing existential crisis. So we bunkerdown. We get protective. We start behaving like survivors rather than explorers. Itʼs our defense mechanism in a world that constantly feels like its is tearing our worldview apart.What we desperately seek a way to to make sense of it all once again.
  • 119. We need a means tomake sense of complexityand respond creatively.What we need is a means to make sense of complexity and respond to it creatively.This is a design challenge. Which I why I loved that this conference is called designing the new economy.
  • 120. As I look at this chair, I canʼt help but see a potential means. What we need in our world is not just the ability to create, collect and store more information but to more quickly makesense of it and exploit it. The human mind stands alone in being able to do this. But alone itʼs not good enough.Thatʼs why this chair matters. It gives us a peek at how integrating the processing robustness of the human mind, the collective intelligence of a community, and the processingefficiency of a computer helps us make sense of and creatively respond to our increasingly complex world.This new kind of technology will potentially be one we use as casually and comfortably as we use MS Word today. It will have an interface. It will have a list of community networksto use just like a list of fonts today. It will offer different algorithms to run on the communities. It will have a mobile app version. It will be used by professional and amateurs.With it, we can solve 30 years old medical mysteries in 3 weeks and provide personal, customized nutritional services to those who canʼt afford them.This is more important than the introduction of the mass assembly line. Because it is about knowledge creation, sense making, and creativity. It will change the economy. And thefirst people that need to get on board is designers. Because we are the people who have always found ways to make new technologies work for the collective betterment of society.
  • 121. ChallengingThis is a frontier that Iʼm excited toexplore because itʼs challenging...
  • 122. Filled with Fascination...filled withfascination...
  • 123. Unpredictable...unpredictable...
  • 124. Filled with Achievement...filled withachievement...
  • 125. Not Destructive or Perilous...notdestructive orperilous...
  • 126. Demanding of Creativity..demandsourcreativity...
  • 127. Sounds RidiculousBut most importantly, it is a frontier that sounds absolutely ridiculous. And thatʼs perfect —because it makes me feel the same way I did at 9 years old when I saw my first brutalistbuilding.
  • 128. That is the explorationthat awaits you!Not mapping stars, butcharting the unknownpossibilities of existence.Leonard Nimoy@leemaschmeyer lee@collins1.comThankyou.